Overview
The Adolescent Brain Cognitive Development (ABCD) dataset aims to map the structural and functional connectivity of the human brain in healthy young adults using high-resolution neuroimaging and behavioral assessments.
Official Website: abcdstudy.org
Data Available in Mind Data Hub
Below, we summarize the modalities and number of subjects processed and available for request in Mind Data Hub:
Structural MRI (T1-weighted & T2-weighted)
Preprocessing Steps:
- Conversion to NIfTI format (If needed)
- Brain Extraction
- Registration to MNI Space using ANTs (Rigid + Affine transformations)
- Quality Control (QC)
Data Available:
- T1-weighted scans: 20,988 records from 11039 unique subjects
- T2-weighted scans: 14,845 records from 11039 unique subjects
Metadata:
Comprehensive demographic.
Metadata Source Files (1 main file):
- Primary Demographics Source: /simurgh/group/BWM/DataSets/ABCD/metadata/demo.csv
- 48,807 total records - Comprehensive demographics including age, sex, race, ethnicity, socioeconomic factors
Key Features:
- Age provided as continuous numeric values (birth date based)
- Subject IDs in BIDS format (sub-NDARINV...)
- Rich demographic data, including race, ethnicity, and parental information
- Multiple timepoints supported (baseline, 1-year, 2-year, etc.)
| Column Name | Description |
|---|---|
subjectId |
Subject identifier in BIDS format (e.g., sub-NDARINV003RTV85) |
sessionName |
Session identifier (e.g., ses-baselineYear1Arm1, ses-followUpYear2Arm1, etc.) |
MNI_Warped |
Path to MNI warped brain image |
MNI_ZSCORE |
Path to Z-score normalized brain image |
MNI_Z_Cropped |
Path to cropped Z-score normalized brain image |
age |
Child’s age at the time of scan (continuous numeric value) |
sex |
Sex assigned at birth (1 = Male, 2 = Female, 3 = Intersex-male, 4 = Intersex-female) |
gender_identity |
Gender identity (1 = Male, 2 = Female, 3 = Trans male, 4 = Trans female, 5 = Non-binary, 6 = Other) |
grade_level |
Current school grade level (e.g., 5.0 = 5th grade) |
hispanic_ethnicity |
Hispanic/Latino ethnicity (1 = Yes, 2 = No) |
race |
Race (1 = White, 2 = Black, 3 = Asian, 4 = Native, 5 = Pacific Islander, 6 = Multiple, 0 = Missing) |
primary_caregiver |
Role of the primary caregiver (1 = Bio mother, 2 = Bio father, etc.) |
parent_age |
Age of the primary caregiver |
parent_income |
Household income category |
language_spanish |
Parent survey language (0 = English, 1 = Spanish) |
partner_education |
Education level of the partner (other parent or caregiver) |
partner_employment |
Employment status of the partner |
Encoding Dictionaries:
- Sex: 1 = Male, 2 = Female, 0 = Unknown
- Ethnicity: 0 = Unknown, 1 = Non-Hispanic, 2 = Hispanic
- Race: 0 = Unknown, 1 = White, 2 = Black, 3 = Asian, 4 = Pacific Islander, 6 = Multiple, 7 = Native American
Encoding Dictionaries:
- Sex Encoding: 1=Male, 2=Female, 0=Unknown
Age Distribution:
- Mean age: ~10 years (baseline cohort)
- Age range: 9-11 years at baseline
- Longitudinal follow-up: 1-year, 2-year, 3-year, 4-year timepoints
Sex Distribution:
- Male: ~52% of subjects
- Female: ~48% of subjects
Race Distribution:
- White: Majority population
- Black/African American: Significant representation
- Asian: Moderate representation
- Other categories: Native American, Pacific Islander
Download Data Date: March 2025
Functional MRI (Resting-state fMRI)
Preprocessing Steps (fMRIPrep):
- Conversion to NIfTI (BIDS format)
- Slice-timing and motion correction
- Brain extraction and normalization to MNI
- Denoising and smoothing
- Quality Control (QC) and time-series extraction
Data Available:
- fMRI scans processed using fMRIPrep: 497 Subjects.
- Comprehensive QC files.
Dedicated scripts are available for both BIDS conversion and parcellation:
- An automated script converts raw imaging data to the standardized BIDS format. Access BIDS conversion script (GitHub)
- A separate script is provided for parcellation calculations. Access parcellation script (GitHub)
Download Data Date: April 2024.
Diffusion Tensor Imaging (DTI)
Preprocessing Steps:
- Convert DICOM to NIfTI
- Topup Correction (Using a top-up tool from FSL)
- Eddy Correction (Using eddy tool from FSL)
- Brain Extraction (Using Bet tool from FSL)
- Merging of Acquisitions (If the session is split into multiple scans)
- DTI Model Fitting(Using the Dtifit tool from FSL)
- Registration to MNI Space using ANTs (Rigid + Affine transformations)
- QC
Download Data Date: March 2025
Request Access to ABCD Data
To request access to ABCD data, please fill out our internal request form. Requests will be reviewed by our data management team.
Citation and Acknowledgment
When using ABCD data, please cite the official ABCD project and acknowledge the Mind Data Hub preprocessing pipeline:
“Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) database (abcdstudy.org). The preprocessing and harmonization of data were performed by Mind Data Hub at Stanford University.”
Useful Links